Topics in astrostatistics: stellar binary evolution, gravitational – wave source modelling and stochastic processes

Barrett, James William (2018). Topics in astrostatistics: stellar binary evolution, gravitational – wave source modelling and stochastic processes. University of Birmingham. Ph.D.

[img]
Preview
Barrett18PhD.pdf
PDF - Accepted Version

Download (7MB)

Abstract

The effective use of statistical techniques is one of the cornerstones of modern astrophysics. In this thesis we use sophisticated statistical methodology to expand our understanding of astrophysics. In particular, we focus on the physics of coalescing binary black holes, and the observation of these events using gravitational-wave astronomy. We use Fisher matrices to explore how much we expect to learn from gravitational-wave observations, and then use machine learning techniques, including random forests and Gaussian processes, to facilitate an otherwise intractable Bayesian comparison of real observations to our model. Finally, we develop a technique based on Gaussian processes for characterising stochastic variability in time series data.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Supervisor(s):
Supervisor(s)EmailORCID
Farr, WillUNSPECIFIEDUNSPECIFIED
Mandel, IlyaUNSPECIFIEDUNSPECIFIED
Licence:
School/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
Department: School of Physics and Astronomy
Funders: Science and Technology Facilities Council
Subjects: Q Science > QB Astronomy
URI: http://147.188.217.239/id/eprint/8203

Actions

Request a Correction Request a Correction
View Item View Item

Downloads

Downloads per month over past year